Applications of parallel genetic algorithms to heat conduction inverse problems

被引：0
|
作者：
Guo, QP [1 ]
Shen, DC [1 ]
机构：
[1] Wuhan Univ Technol, Wuhan 430070, Peoples R China
来源：
DCABES AND ICPACE JOINT CONFERENCE ON DISTRIBUTED ALGORITHMS FOR SCIENCE AND ENGINEERING | 2005年
关键词：
heat conduction; inverse problem; parallel genetic algorithm; parallel computing;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A parallel genetic algorithm (PGA) is applied to an established mathematical model of inverse problems in 2-D heat conduction defined with either known boundary conditions or temperature measurements. Numerical experiments show that PGA is a feasible and effective optimization tool for heat conduction inverse problems. The PGA combines the high-speed parallel-ability of supercomputers and the inherent parallel properties of GA showing significant improvements in efficiency and accuracy compared to sequential GAs.
引用
收藏
页码：47 / 51
页数：5
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